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Found 4 papers, 0 papers with code
Eeg2vec: Self-Supervised Electroencephalographic Representation Learning
Recently, many efforts have been made to explore how the brain processes speech using electroencephalographic (EEG) signals, where deep learning-based approaches were shown to be applicable in this field.
Trend-Based SAC Beam Control Method with Zero-Shot in Superconducting Linear Accelerator
To validate the effectiveness of our method, two different typical beam control tasks were performed on China Accelerator Facility for Superheavy Elements (CAFe II) and a light particle injector(LPI) respectively.
Learning Incrementally to Segment Multiple Organs in a CT Image
In each incremental learning (IL) stage, we lose the access to previous data and annotations, whose knowledge is assumingly captured by the current model, and gain the access to a new dataset with annotations of new organ categories, from which we learn to update the organ segmentation model to include the new organs.
Coordinated Frequency Control through Safe Reinforcement Learning
With widespread deployment of renewables, the electric power grids are experiencing increasing dynamics and uncertainties, with its secure operation being threatened.
